The term “arteriosclerosis” is a general term for diseases characterized by arterial wall thickening caused by a variety of factors such as aging and lifestyle habits, decreased artery elasticity, and inner-cavity stenosis. Arteriosclerosis proceeds over a long period of time without subjective symptoms, inducing cardiac diseases such as myocardial infarction or cerebrovascular diseases such as cerebral infarction or cerebral-hemorrhage. Therefore, it is important to develop a method for conveniently and accurately assaying with certainty the severity and the extent of arteriosclerosis and therapeutic effects against arteriosclerosis. Conventionally, assays using as indicators, in addition to blood pressure levels or lipid marker levels (total serum cholesterol level, high LDL cholesterol level, and low HDL cholesterol level), blood concentrations of inflammatory markers including a high sensitive C-reactive protein (hs-CRP), serum amyloidA (SAA), an oxidant stress-related factor homocystine, and the like have been examined in many epidemiological studies. However, since the levels of these factors vary in other diseases, a search for a more selective marker with high disease specificity has been an issue. Arteriosclerosis follows the multifaceted processes of lipid deposition in vascular intima, inflammatory cell infiltration, smooth muscle cell proliferation, foam cell formation of macrophage and/or smooth muscle cells, interstitial matrix formation, and the like. It has been demonstrated that in each process, various factors are synergistically involved in progression of lesions (Non-patent document 1). An assay with a combination of a plurality of markers is thought to be effective for accurately assessing pathogenesis.
Disease proteomics is a technique for exhaustively searching for an increase or a decrease in protein level, which varies depending on the specific disease, compared with a healthy state, using a body fluid such as blood, saliva, or urine, or a tissue sample, as a material. Disease proteomics is characterized by being capable of simultaneously extracting and/or detecting a plurality of factors with unknown relationships to the disease. Application of multiple specimens to and increased sensitivity of a 2D electrophoresis method and measuring apparatuses such as a protein microarray and mass spectrometry have been realized, and data analysis technology has been in place, which have been applied for searching markers for various diseases including cancer, immunity disorders, infections, and the like (Non-patent document 2).